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边缘型人格障碍的情感不稳定:你所知道的会影响你的感受。

Borderline personality disorder affective instability: What you know impacts how you feel.

机构信息

Department of Psychology, Suffolk University.

出版信息

Personal Disord. 2018 Jul;9(4):369-378. doi: 10.1037/per0000280. Epub 2018 Feb 19.

Abstract

The current study examined the role of conceptual knowledge and language in affective instability (AI) associated with borderline personality disorder (BPD). Forty-six females meeting criteria for BPD and 51 nonclinical female control participants without BPD completed a measure of general vocabulary and a semantic similarities task that provided estimates of the degree to which participants weighted information about valence and arousal in their understanding of emotion language. Feelings of valence and arousal were assessed using the Self-Assessment Manikin in response to 62 emotionally evocative images, which was used to derive estimates of AI. BPD status was associated with valence and arousal AI at a bivariate level, but not after controlling for language variables (general vocabulary and semantic valence and arousal foci). Participants with stronger as opposed to weaker vocabularies exhibited less AI, and participants who emphasized arousal more in their conceptual representations of emotions exhibited less AI than those who emphasized it to a lesser degree. With the inclusion of language variables in a regression equation with BPD status predicting AI, semantic arousal focus, but not general vocabulary, was a significant predictor of AI. Consistent with psychological constructionist models of emotion that specify an active role of language throughout the emotion generation process, these findings suggest that language capacity (general vocabulary and the degree to which arousal influences understanding of emotion words) is an important determinant of the AI associated with BPD. (PsycINFO Database Record

摘要

当前的研究考察了概念知识和语言在与边缘型人格障碍(BPD)相关的情感不稳定(AI)中的作用。46 名符合 BPD 标准的女性和 51 名无 BPD 的非临床女性对照组参与者完成了一般词汇量的测量和语义相似性任务,该任务提供了参与者在理解情感语言时对价值和唤醒信息进行加权的程度的估计。使用自我评估情绪图来评估价值和唤醒感,该图用于得出 AI 的估计值。在双变量水平上,BPD 状态与价值和唤醒 AI 相关,但在控制语言变量(一般词汇量和语义价值和唤醒焦点)后则不然。与词汇量较弱的参与者相比,词汇量较强的参与者表现出较少的 AI,并且与那些对其情绪概念表示强调程度较低的参与者相比,那些在其概念表示中更强调唤醒的参与者表现出较少的 AI。在包含语言变量的回归方程中,将 BPD 状态预测 AI,语义唤醒焦点,但不是一般词汇量,是 AI 的重要预测指标。这些发现与情感的心理建构主义模型一致,该模型指定语言在整个情感生成过程中发挥积极作用,表明语言能力(一般词汇量和唤醒度对理解情感词汇的影响程度)是与 BPD 相关的 AI 的重要决定因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e287/6033624/e5e359fd4634/nihms916857f1.jpg

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